- COURSE
Develop Natural Language Solutions in Azure (AI-3003)
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Certification:
Exam:
Continuing Education Credits:
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Natural language solutions use language models to interpret the semantic meaning of written or spoken language, and in some cases respond based on that meaning. You can use the Language service to build language models for your applications, and explore Azure AI Foundry to use generative models for speech.
Upcoming Class Dates and Times
All Sunset Learning courses are guaranteed to run
Course Outline and Details
Prerequisites
Before starting this learning path, you should already have:
- Familiarity with Azure and the Azure portal.
- Experience programming with C# or Python. If you have no previous programming experience, we recommend you complete the Take your first steps with C# or Take your first steps with Python learning path before starting this one.
Target Audience
- Database Professional
- Microsoft Professional
Course Objectives
In this course you’ll learn-
- Analyze text with Azure AI Language
- Create question answering solutions with Azure AI language
- Build a conversational language understanding model
- Create a custom text classification solution
- Custom named entity recognition
- Translate text with Azure AI Translator service
- Create speech-enabled apps with Azure AI services
- Translate speech with the Azure AI Speech service
- Develop an audio-enabled Generative AI application
Course Outline
Analyze text with Azure AI Language
- Provision an Azure AI Language resource
- Detect language
- Extract key phrases
- Analyze sentiment
- Extract entities
- Extract linked entities
- Exercise – Analyze text
Create question answering solutions with Azure AI language
- Understand question answering
- Compare question answering to Azure AI Language understanding
- Create a knowledge base
- Implement multi-turn conversation
- Test and publish a knowledge base
- Use a knowledge base
- Improve question answering performance
- Exercise – Create a question answering solution
Build a conversational language understanding model
- Understand prebuilt capabilities of the Azure AI Language service
- Understand resources for building a conversational language understanding model
- Define intents, utterances, and entities
- Use patterns to differentiate similar utterances
- Use pre-built entity components
- Train, test, publish, and review a conversational language understanding model
- Exercise – Build an Azure AI services conversational language understanding model
Create a custom text classification solution
- Understand types of classification projects
- Understand how to build text classification projects
- Exercise – Classify text
Custom named entity recognition
- Understand custom named entity recognition
- Label your data
- Train and evaluate your model
- Exercise – Extract custom entities
Translate text with Azure AI Translator service
- Provision an Azure AI Translator resource
- Understand language detection, translation, and transliteration
- Specify translation options
- Define custom translations
- Exercise – Translate text with the Azure AI Translator service
Create speech-enabled apps with Azure AI services
- Provision an Azure resource for speech
- Use the Azure AI Speech to Text API
- Use the text to speech API
- Configure audio format and voices
- Use Speech Synthesis Markup Language
- Exercise – Create a speech-enabled app
Translate speech with the Azure AI Speech service
- Provision an Azure resource for speech translation
- Translate speech to text
- Synthesize translations
- Exercise – Translate speech
Develop an audio-enabled Generative AI application
- Deploy a multimodal model
- Develop an audio-based chat app
- Exercise – Develop an audio-enabled chat app